6-2: Visualizing Spatial Data using ArcGIS API for Python#

1. Introduction to the ArcGIS API for Python#

  • The ArcGIS API for Python, i.e., the arcgis package, is a powerful, modern and easy to use Pythonic library to perform GIS visualization and analysis, spatial data management and GIS system administration tasks that can run both in an interactive fashion, as well as using scripts.

  • Shipped with the ArcGIS Pro installation file

Helpful resource on arcgis:

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1.1 Import the package#

import arcgis

from arcgis import GIS, GeoAccessor, GeoSeriesAccessor, pd

1.2 The GIS class from the gis module#

  • what is class in Python?

    • it is a blueprint for building things (a machine produces products)

    • things get created from the class are called objects (or instances of the class)

    • DRY (Don’t repeat yourself) code.

    • example:

      • a college student

      • a data structure that organizes the data – NumPy array and pandas DataFrame

  • what is gis (Geographic Information System)?

    • Geographic Data:

      • collection

      • storage

      • manipulation

      • analysis

      • visualization

      • management/administration

      • distribution

    • A variety of technologies:

      • human activities (such as conducting survey of a area of land)

      • hardware

      • software (a narrower definition of GIS)

  • The GIS class

    • from the gis module (the core) of the arcgis package

    • a portal to do GIS

    • can link to an ArcGIS Online account

    • or, be used locally without the connection

2. Spatially Enabled DataFrame (SEDF)#

2.1 What is SEDF#

  • A class from the features module of arcgis (arcgis.features)

    • contains types and functions for working with features and feature layers in the GIS.

  • An extension of the DataFrame class from pandas

  • we use ArcPy as the geometry engine for this module, which gives us access to all native GIS data ArcGIS Pro supports

2.2 Load a feature class as SEDF#

from arcgis import pd, GeoAccessor, GeoSeriesAccessor
import arcpy

gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp
blkgrp_fc = "blockgroups"

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp_fc)
blkgrp_sedf.head()
OBJECTID STATEFP10 COUNTYFP10 TRACTCE10 BLKGRPCE10 GEOID10 NAMELSAD10 MTFCC10 FUNCSTAT10 ALAND10 ... DEN_NOTWEL DEN_NOTATA PCT_OWN5 PCT_RENT5 PCT_BACHLR PCT_POV PCT_RU1 DATAYEAR DESCRIPT SHAPE
0 1 12 023 110903 2 120231109032 Block Group 2 G5030 S 57546992.0 ... 0.004918 0.000000 17.225951 62.878788 9.922481 23.488372 23.488372 REDISTRICTING, SF1, ACS 2010 120231109032 {"rings": [[[530441.2199999988, 651631.75], [5...
1 2 12 023 110904 1 120231109041 Block Group 1 G5030 S 85591551.0 ... 0.000329 0.000329 26.212320 58.015267 5.456656 4.102167 4.102167 REDISTRICTING, SF1, ACS 2010 120231109041 {"rings": [[[534712.1700000018, 663369.54], [5...
2 3 12 007 000300 5 120070003005 Block Group 5 G5030 S 196424609.0 ... 0.000021 0.000000 13.270142 68.181818 1.254613 10.701107 10.701107 REDISTRICTING, SF1, ACS 2010 120070003005 {"rings": [[[567924.9299999997, 665800.79], [5...
3 4 12 007 000300 4 120070003004 Block Group 4 G5030 S 16339411.0 ... 0.000000 0.000000 18.924731 73.711340 12.617839 14.902103 14.902103 REDISTRICTING, SF1, ACS 2010 120070003004 {"rings": [[[588576.3599999994, 644359.46], [5...
4 5 12 007 000300 1 120070003001 Block Group 1 G5030 S 57089369.0 ... 0.000000 0.001138 22.957198 43.333333 1.134021 21.161826 21.161826 REDISTRICTING, SF1, ACS 2010 120070003001 {"rings": [[[576256.1799999997, 656541.8300000...

5 rows × 202 columns

len(blkgrp_sedf)  # recall

178

blkgrp_sedf.shape  # recall

(178, 202)

blkgrp_sedf['TOTALPOP'].values

array([2094, 2269, 1305, 1991, 2056, 1410, 1890, 2510, 1150, 1856, 1455,
       1905, 2703,  865, 1735, 2330,  979, 1169, 2186, 3172,  163, 2175,
       2139, 2162,  999, 2124, 2278, 1600,  323, 2558, 2452, 1814, 4757,
       3260,  710,  911, 1391,  866, 2755,  798, 1937, 1166, 1246, 2329,
        924, 1779,  885,  665,  803,  844, 1418,  770, 1430,  568, 1193,
       1440,  777, 1806,  821, 1627, 1347, 1058, 2112, 1391, 1502, 1232,
       3088, 1077, 1174, 1155, 1582, 1130,  625, 1165, 1090, 1210, 2285,
       2171, 1604, 1957,  620, 1091, 1196,  642, 3589, 1433, 2906, 1930,
       5398, 1414, 1033,  993, 1345, 1482,  787, 1157, 1962, 1658, 1570,
       1973, 3617, 1270, 2497, 1522, 1356, 2877, 1323, 1741,  682,  833,
       1364,  895, 2482,  962,  838, 2136, 1567, 1255, 2030, 1269, 1154,
       1488, 2180,  703, 1066, 1861, 1515, 2027, 1061, 1067, 1851, 1614,
       1363, 1779, 1685, 1784,  696,  866, 1638, 1684, 3282, 1462,  386,
       2040,  662, 3641, 1431,  718, 2888, 1846, 2559, 1619, 1538,  963,
       2463,  696, 1070, 3415, 2034, 2613, 1138,  823, 3886, 2662, 2625,
        823,  836,  978, 1091,  637,  921, 1342, 2680, 1211, 1788, 1723,
       1189,  789], dtype=int64)

3. Visualizing GIS data#

3.1 Create a map#

  1. Import all the necessary modules

from arcgis import GIS, GeoAccessor, GeoSeriesAccessor, pd

  1. Create a GIS instance

my_gis = GIS()

my_gis
GIS @ https://www.arcgis.com

  1. Load data in the “GIS” as SEDF

import arcpy
gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp

blkgrp = "blockgroups"
schools = 'schools'

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp)
schools_sedf = pd.DataFrame.spatial.from_featureclass(schools)

  1. Use the map widget from the GIS instance to create a map

# call the map() function from the GIS instance
my_map_in_my_gis = my_gis.map(location=[29.7, -82.3], zoomlevel=9)

my_map_in_my_gis

  1. Load SEDFs into the map

  • call spatial.plot() from the sedf

  • last loaded sedf will be displayed on the top

blkgrp_sedf.spatial.plot(map_widget=my_map_in_my_gis)

True

schools_sedf.spatial.plot(map_widget=my_map_in_my_gis,
                          col='NAME', 
                          renderer_type='u')

True

3.2 Modify the size of the widget window#

from ipywidgets import Layout

my_map_in_my_gis.layout = Layout(height="600px")

my_map_in_my_gis.layout = Layout(width="600px", height="600px")

my_map_in_my_gis

3.3 Change the Basemap#

  1. basemaps attribute of a map returns a list of available basemaps

my_map_in_my_gis.basemaps

['dark-gray',
 'dark-gray-vector',
 'gray',
 'gray-vector',
 'hybrid',
 'national-geographic',
 'oceans',
 'osm',
 'satellite',
 'streets',
 'streets-navigation-vector',
 'streets-night-vector',
 'streets-relief-vector',
 'streets-vector',
 'terrain',
 'topo',
 'topo-vector']

my_map_in_my_gis

  1. Set basemap by assign a value in the list to the basemap attribut.

my_map_in_my_gis.basemap = 'dark-gray'

3.4 Choropleth Map#

from arcgis import mapping

mapping.display_colormaps()
../_images/6-2.Intro_to_ArcGIS_API_for_Python_39_0.png 
map2 = my_gis.map(location=[29.7, -82.3], zoomlevel=10)

blkgrp_sedf.spatial.plot(map_widget=map2, colors="YlGnBu",
                         col='TOTALPOP', renderer_type='c',
                         method='esriClassifyNaturalBreaks',
                         class_count=7)

True

from ipywidgets import Layout
map2.layout = Layout(height="700px")

map2